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» Generalizing Parametricity Using Information-flow
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CVPR
2011
IEEE
13 years 6 months ago
Saliency Estimation Using a Non-Parametric Low-Level Vision Model
Many successful models for predicting attention in a scene involve three main steps: convolution with a set of filters, a center-surround mechanism and spatial pooling to constru...
Naila Murray, Maria Vanrell, Xavier Otazu, C. Alej...
ENTCS
2008
125views more  ENTCS 2008»
13 years 9 months ago
Quantum Arrows in Haskell
We argue that a realistic model for quantum computations should be general with respect to measurements, and complete with respect to the information flow between the quantum and ...
Juliana Kaizer Vizzotto, Antônio Carlos da R...
KDD
2007
ACM
237views Data Mining» more  KDD 2007»
14 years 9 months ago
Knowledge discovery of multiple-topic document using parametric mixture model with dirichlet prior
Documents, such as those seen on Wikipedia and Folksonomy, have tended to be assigned with multiple topics as a meta-data. Therefore, it is more and more important to analyze a re...
Issei Sato, Hiroshi Nakagawa
ICCAD
2006
IEEE
127views Hardware» more  ICCAD 2006»
14 years 6 months ago
Joint design-time and post-silicon minimization of parametric yield loss using adjustable robust optimization
Parametric yield loss due to variability can be effectively reduced by both design-time optimization strategies and by adjusting circuit parameters to the realizations of variable...
Murari Mani, Ashish Kumar Singh, Michael Orshansky
ICIP
2009
IEEE
14 years 10 months ago
Model-based Shape Recovery From Single Images Of General And Unknown Lighting
We present a new statistical shape-from-shading framework for images of unknown illumination. The object (e.g., face) to be reconstructed is described by a parametric model. To de...